SignComm captures sign language gestures and translates them into text and speech in real time — using XR and AI to bridge the gap between signers and non-signers.
AI detects gestures through headset sensors, translating them into text and speech instantly and accurately.
Works across XR devices, smartphones, browsers, kiosks, and smart glasses.
Starts with ASL, expanding to 200+ sign languages as the model grows.
The user launches SignComm on an XR headset.
Gestures are followed in real time through camera data.
Gestures become text and speech, shown as live captions.
Confidence scores update frame by frame, so unclear signs are flagged before they reach the caption.
Movement paths, speed, and hand orientation are measured together to separate similar-looking signs.
Every corrected translation feeds back into the model, so recognition keeps improving with the people who use it.
Over 70 million people rely on sign language to communicate, yet most services, classrooms, and workplaces remain inaccessible to them.
SignComm exists to close that gap — not by asking signers to adapt, but by teaching everyday devices to understand them.
The people who sign every day shape what we build. Every model update is reviewed with Deaf educators and interpreters before it ships.
SignComm is currently in development.
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